Saif Vazir
About Saif Vazir
Saif Vazir is a Machine Learning Engineer with experience in developing machine learning and computer vision solutions, particularly in the manufacturing sector. He holds a Master of Science in Computer Science from Stony Brook University and has contributed to significant projects in healthcare and technology.
Work at Tulip
Currently, Saif Vazir serves as a Machine Learning Engineer at Tulip Interfaces, a position he has held since 2020. In this role, he focuses on developing machine learning and computer vision solutions tailored for the manufacturing industry. His work involves creating innovative applications that enhance operational efficiency and productivity. Vazir has also contributed to the deployment of machine learning models optimized for low-power devices, ensuring effective performance in edge computing environments.
Education and Expertise
Saif Vazir holds a Master of Science in Computer Science from Stony Brook University, which he completed from 2018 to 2019. Prior to that, he earned a Bachelor of Technology in Computer Engineering from Veermata Jijabai Technological Institute (VJTI) between 2014 and 2018. His educational background equips him with a solid foundation in computer science principles, machine learning, and software development. Vazir has expertise in creating user interfaces and back-end software using technologies such as React, Typescript, and Golang.
Background
Saif Vazir began his professional journey with internships at Avanti Learning Centres in 2015 and SAMSUNG R&D INSTITUTE INDIA - BANGALORE PRIVATE LIMITED in 2017. These experiences provided him with valuable insights into the tech industry. Following his academic pursuits, he worked as a Computer Vision Intern at Tempus, Inc. in 2019, where he contributed to significant projects in the healthcare domain, including image registration and semantic segmentation.
Achievements
Saif Vazir has co-authored two notable papers in the field of computer vision. The first paper, titled 'Forward Propagation, Backward Regression, and Pose Association for Hand Tracking in the Wild,' explores advanced techniques in hand tracking. The second paper, 'WorkingHands: A Hand-Tool Assembly Dataset for Image Segmentation and Activity Mining,' presents a dataset aimed at enhancing image segmentation and understanding of activity mining in practical applications.
Projects at Tempus Labs Inc.
During his tenure at Tempus Labs Inc., Saif Vazir contributed to key projects that involved image registration of giga-pixel resolution images and semantic segmentation of tissue samples. These projects are significant in the healthcare domain, as they enhance the analysis and interpretation of medical images, ultimately supporting better patient outcomes.